How to Read CSV Files with NumPy? Last Updated : 26 Apr, 2025 Comments Improve Suggest changes Like Article Like Report Reading CSV files is a common task when working with data in Python. In this article we will see how to read CSV files using Numpy's loadtxt() and genfromtxt() methods.1. Using NumPy loadtxt() methodThe loadtext() method is faster and simpler for reading CSV files. It is best when the file has consistent columns and no missing values.Syntax: numpy.loadtxt('filename.csv', delimiter=',', dtype=str)Parameters:filename: File name or path link to the CSV file.delimiter (optional): Delimiter to consider while creating array of values from text default is whitespace.encoding (optional): Encoding used to decode the input file.dtype (optional): Data type of the resulting arrayReturn: Returns a NumPy array.We will be using Numpy library for its implementation. You can download the sample dataset from here. Python import numpy as np arr = np.loadtxt("/content/CAR.csv", delimiter=",", dtype=str) display(arr) Output:Using numpy's loadtxt()2. Using NumPy genfromtxt() methodThe genfromtxt() function is used to handle datasets with missing values or varied data types. It's perfect for more complex CSV files that require handling.Syntax: numpy.genfromtxt('filename.csv', delimiter=',', dtype=None, skip_header=0, missing_values=None, filling_values=None, usecols=None)Parameters:filename: File name or path to the CSV file.delimiter (optional): Used consider while creating array of values from text default is any consecutive white spaces act as a delimiter.missing_values (optional): Set of strings to use incase of a missing value.dtype (optional): Data type of the resulting array.Return: Returns NumPy array. Python import numpy as np arr = np.genfromtxt("/content/CAR.csv", delimiter=",", dtype=str) display(arr) Output:Using numpy's genfromtxt() By using NumPy’s loadtxt() and genfromtxt() methods we can efficiently read and process CSV files whether they are simple or contain complex data structures this makes NumPy a good choice for data analysis tasks. Comment More infoAdvertise with us Next Article How to Read CSV Files with NumPy? E error_502 Follow Improve Article Tags : Python Python-numpy Practice Tags : python Similar Reads How to Efficiently Read File with Numba? Numba is a powerful library in Python that allows users to write high-performance, compiled code. It is particularly useful for numerical and scientific computing, where speed and efficiency are crucial. One of the essential tasks in any data processing pipeline is reading files, and Numba provides 6 min read How to Read Text Files with Pandas? In this article, we will discuss how to read text files with pandas in Python. In Python, the Pandas module allows us to load DataFrames from external files and work on them. The dataset can be in different types of files.Text File UsedRead Text Files with PandasBelow are the methods by which we can 6 min read How to read numbers in CSV files in Python? Prerequisites: Reading and Writing data in CSV, Creating CSV files CSV is a Comma-Separated Values file, which allows plain-text data to be saved in a tabular format. These files are stored in our system with a .csv extension. CSV files differ from other spreadsheet file types (like Microsoft Excel 4 min read How to Read CSV File in Ruby? It is common to have tabular data stored in CSV (Comma Separated Values) files. In Ruby, one can handle CSV files without much ado because the built-in libraries make it easy to do so. This article focuses on discussing the ways to read a CSV file in Ruby. Approach to Read CSV Files in Ruby?There ar 2 min read How To Load Csv File In Jupyter Notebook? Loading a CSV file in Jupyter Notebook is an important step for data analysis and manipulation. Pandas library provides an easy way to read CSV files and work with tabular data in Python. Let's see how we can load csv file.Step 1: Install Pandas LibraryMake sure we have installed Pandas Library, if 2 min read Like